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RISS 인기검색어
- 검색키워드
- 저자 : Arul U. (검색결과 3 건)
- 무료
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- 유료
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Effective Anomaly Identification in Surveillance Videos Based on Adaptive Recurrent Neural Network
Arul U.,Arun V.,Rao T. Prabhakara,Baskaran R.,Kirubakaran S.,Hussan M. I. Thariq 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.3
Surveillance systems completed in true environment are of a solid nature. As the environment is uncertain and variable, care gradually becomes confusing when moving away from a stable and controlled environment. Evidence to distinguish stressful abnormalities in video surveillance is a problematic issue due to leakage, video screaming, contradictions and motives. Hence, in this paper, adaptive recurrent neural network is developed for anomaly detection from the videos. The projected technique is a combination of recurrent neural network and crystal structure algorithm. In the anomality detection, the video should be changed into frames. After that, the images should be enhanced for improving image quality. Once, the image quality is enhanced, the image background should be eliminated for achieving object detection. In the proposed technique, the region of interest is utilized to attain the object detection step in the images. The detected object images are used to tracking the object in the images by using the proposed classifer. To enhance the object tracking system, the feature extraction is a required topic in the system. Maximally stable extremal regions is used to extract the required features from the images. Finally, the proposed classifer is utilized to achieve anomaly detection based on object movement in the input images. The projected strategy is implemented and evaluated by performance metrices. It is contrasted with conventional techniques such as convolutional neural network-particle swarm optimization (CNN-PSO) and CNN respectively.
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Concrete Confinement Effect in Circular Concrete Sandwiched Double Steel Tubular Stub-Columns
U. Mashudha Sulthana,S. Arul Jayachandran 한국강구조학회 2020 International Journal of Steel Structures Vol.20 No.4
Concrete sandwiched double steel tubular (CSDST) columns have improved ductility under cyclic loads. Two CSDST columns are investigated in this paper (1) CSDST-CS with Circular outer tube and Square inner tube and (2) CSDST-CC with Circular outer tube and Circular inner tube. The confi nement of concrete between the annular spaces of the inner and outer tubes is very important for their behaviour. To the authors’ knowledge, the literature is scarce on a validated concrete confi nement model for CSDST. In this paper, the concrete confi nement mechanism in CSDST columns is explained based on thick-walled cylinder theory and a semi-analytical equation is developed. Hollowness ratio of the cross-section, width to thickness ratio of the outer steel tube, strength of the outer steel tube and sandwiched concrete strength are identifi ed as the main parameters infl uencing the confi nement eff ect in CSDST. The proposed equation is extended to CSDST-CS with inner square tube approximated as an equivalent circular tube. This assumption is validated by conducting tests on short column specimens under axial compression. With outer tubes being the same, concrete confi nement eff ect in CSDST-CS, CSDSTCC and concrete fi lled steel tubular column (CFST) are 18%, 20% and 30%, respectively. This study has demonstrated that the presence of double steel tubes does not improve the concrete confi nement in CSDST compared to CFST. Further, this study presents a modifi cation to the design equations of EN 1994-1-2 2005-1-1 (Eurocode 4: Design of composite steel and concrete structures Part 1–1: General rules and rules for buildings. European Committee for Standardization, Brussels, 2004) for CFST columns to CSDST stub columns by incorporating the eff ect of hollowness.
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Yun, D.Y.,Arul, N.S.,Lee, D.U.,Lee, N.H.,Kim, T.W. Elsevier Science 2015 ORGANIC ELECTRONICS Vol.24 No.-
Organic bistable devices (OBDs) were fabricated utilizing nanocomposites made from a blend of Cu<SUB>2</SUB>ZnSnS<SUB>4</SUB> (CZTS) nanoparticles within a polymethyl methacrylate (PMMA) matrix on a polyethylene terephthalate substrate. Energy dispersive X-ray spectroscopy profiles, X-ray diffraction patterns, and high-resolution transmission electron microscopy images showed that the polycrystalline CZTS nanoparticles were randomly distributed in the PMMA layer. The current-voltage (I-V) curves at 300K for the fabricated OBDs showed bidirectional switchable and current hysteresis behaviors, indicative of the removal of sneak current paths without an additional layer with characteristics of diode or selector. The removal of the sneak current paths prevented the leakage current of the OBDs, resulting in an increase of the current of high conduction (ON) level. The maximum ON/low-conduction (OFF) ratio of the current bistability for the fabricated OBDs was as large as 1x10<SUP>9</SUP>. The write-read-erase-read sequences of the OBDs showed rewritable nonvolatile memory behaviors. The ON or the OFF states could be retained for 1x10<SUP>5</SUP> cycles, indicative of excellent memory stability. The ON/OFF ratio of 10<SUP>9</SUP> was maintained after 10<SUP>5</SUP> cycles. The memory mechanisms of the fabricated OBDs are described on the basis of the I-V results.
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